def init_attention_weight()

in utils.py [0:0]

• 26 lines of code
• 2 McCabe index (conditional complexity)

def init_attention_weight(
        weights,
        scope,
        c_in,
        k,
        trainable_gamma=True,
        spec_norm=True):

    if spec_norm:
        spec_norm = FLAGS.spec_norm

    atten_weights = {}
    with tf.variable_scope(scope):
        atten_weights['q'] = get_weight(
            'atten_q', [1, 1, c_in, k], spec_norm=spec_norm)
        atten_weights['q_b'] = tf.get_variable(
            shape=[k], name='atten_q_b1', initializer=tf.initializers.zeros())
        atten_weights['k'] = get_weight(
            'atten_k', [1, 1, c_in, k], spec_norm=spec_norm)
        atten_weights['k_b'] = tf.get_variable(
            shape=[k], name='atten_k_b1', initializer=tf.initializers.zeros())
        atten_weights['v'] = get_weight(
            'atten_v', [1, 1, c_in, c_in], spec_norm=spec_norm)
        atten_weights['v_b'] = tf.get_variable(
            shape=[c_in], name='atten_v_b1', initializer=tf.initializers.zeros())
        atten_weights['gamma'] = tf.get_variable(
            shape=[1], name='gamma', initializer=tf.initializers.zeros())

    weights[scope] = atten_weights